class_docstr: A stream that generates the entire history of a stream at each time step.
  
  Parameters
  ----------
  min_periods : int, default 1
      The number of periods to wait before producing values from the aggregation
      function.
code: def __init__(self, min_periods: int = 1) -> None:
      super().__init__()
      self.min_periods = min_periods
      self.history = []
  
imports: from typing import Callable, List
  import numpy
  from tensortrade.feed.core.base import Stream
  from tensortrade.feed.api.float import Float
label_desc: Use image node_id 1 to create a new Expanding object from inherited base classes: Stream with example: obj = Expanding(min_periods)